Please visit @proptechbuzz and support the launch of Inspectica 3.0 - AI Facade Inspection and Lifecycle Maintenance Management for Built Infrastructure. proptechbuzz.com/companies/r…

How we prompt AI is very different in 2026 than 2022 when ChatGPT came out. I'm teaching a new course, AI Prompting for Everyone, to help you become an AI power user — whatever your current skill level. It covers skills that apply across ChatGPT, Gemini, Claude, and other AI tools. How to use deep research mode for well-researched reports on complex questions. How to give AI the right context, including more documents and images than most people realize you can provide. When to ask AI to think hard for several minutes on important decisions like what car to buy, what to study, or what job to take. And how to use AI to generate images, analyze data, and build simple games and websites. I also cover intuitions about how these models work under the hood, so you know when to trust an answer and when not to. Along the way, you'll see flying squirrels, a creativity test, some of my old family photos, and fireworks. Join me at deeplearning.ai/courses/ai-p…

AI-native software engineering teams operate very differently than traditional teams. The obvious difference is that AI-native teams use coding agents to build products much faster, but this leads to many other changes in how we operate. For example, some great engineers now play broader roles than just writing code. They are partly product managers, designers, sometimes marketers. Further, small teams who work in the same office, where they can communicate face-to-face, can move incredibly quickly. Because we can now build fast, a greater fraction of time must be spent deciding what to build. To deal with this project-management bottleneck, some teams are pushing engineer:product manager (PM) some teams are pushing engineer:product manager (PM) ratios downward from, say, 8:1 to as low as 1:1. But we can do even better: If we have one PM who decides what to build and one engineer who builds it, the communication between them becomes a bottleneck. This is why the fastest-moving teams I see tend to have engineers who know how to do some product work (and, optionally, some PMs who know how to do some engineering work). When an engineer understands users and can make decisions on what to build and build it directly, they can execute incredibly quickly. I’ve seen engineers successfully expand their roles to including making product decisions, and PMs expand their roles to building software. The tech industry has more engineers than PMs, but both are promising paths. If you are an engineer, you’ll find it useful to learn some product management skills, and if you’re a PM, please learn to build! Looking beyond the product-management bottleneck, I also see bottlenecks in design, marketing, legal compliance, and much more. When we speed up coding 10x or 100x, everything else becomes slow in comparison. For example, some of my teams have built great features so quickly that the marketing organization was left scrambling to figure out how to communicate them to users — a marketing bottleneck. Or when a team can build software in a day that the legal department needs a week to review, that’s a legal compliance bottleneck. In this way, agentic coding isn’t just changing the workflow of software engineering, it’s also changing all the teams around it. When smaller, AI-enabled teams can get more done, generalists excel. Traditional companies need to pull together people from many specialties — engineering, product management, design, marketing, legal, etc. — to execute projects and create value. This has resulted in large teams of specialists who work together. But if a team of 2 persons is to get work done that require 5 different specialities, then some of those individuals must play roles outside a single speciality. In some small teams, individuals do have deep specializations. For example, one might be a great engineer and another a great PM. But they also understand the other key functions needed to move a project forward, and can jump into thinking through other kinds of problems as needed. Of course, proficiency with AI tools is a big help, since it helps us to think through problems that involve different roles. Even in a two-person team, to move fast, communication bottlenecks also must be minimized. This is why I value teams that work in the same location. Remote teams can perform well too, but the highest speed is achieved by having everyone in the room, able to communicate instantaneously to solve problems. This post focuses on AI-native teams with around 2-10 persons, but not everything can be done by a small team. I'll address the coordination of larger teams in the future. I realize these shifts to job roles are tough to navigate for many people. At the same time, I am encouraged that individuals and small teams who are willing to learn the relevant skills are now able to get far more done than was possible before. This is the golden age of learning and building! [Original text: deeplearning.ai/the-batch/is… ]

Your 'moment of doom' for Apr. 30, 2026 ~ Hot off the press. "... we are willing to make the prediction that 2026 will be the warmest year in the period of instrumental temperature measurements. Of course, 2027 will be still hotter." jimehansen.substack.com/p/20…

The strongest El Niño in 150 years? That’s not hype, it’s the actual median forecast right now for the developing event later this year. It could rival — or even surpass — the legendary 1877 El Niño, the strongest on record, which was linked to widespread drought, monsoon failure, and global food crises in parts of Asia, Africa, and South America. But what does that mean today? It means a tremendous amount of excess ocean heat being released into the atmosphere - energy that can rearrange weather patterns around the world. That typically leads to: 🌧️ Increased flood risk in some regions 🔥 More intense/ prolonged heatwaves, drought and fires 🌪️ A shift in severe storm tracks 🌀 And often a suppressed Atlantic hurricane season, but boosted in the East Pacific. Since it’s so huge, when the Pacific talks, the atmosphere listens! But this isn’t 1877… forecasting, infrastructure, and global awareness are far better today. We’ll be better prepared. Now transparency on the science: the 1877 3-month Nino 3.4 ocean temp anomaly maxed out at 2.7°C. The latest median forecast for all ensembles in late 2026 is 2.75°C in the Nino 3.4 region. So, it may be stronger. Here’s the caveat: that region is now approx .75 - 1°C warmer than it was in 1855, so some of the heat building up there is on top of a baseline which is already warmer today. So in absolutes… this will probably rival 1877, but relatively speaking due to global warming, the event will likely fall short and thus its global impacts may not rise to that level. That’s why we now have the RONI (index) which accounts for our new warmed World. (Pictured here is the October NMME with a region of 3-4°C over the East Tropical Pacific) Will certainly be interesting to watch from a scientific perspective.

We haven’t seen atmospheric CO2 levels consistently this high in 14 MILLION years. We’re in so so SO much trouble, & pretty much every politician & journalist has just decided to ignore it. No time to wait. #ActOnClimate #climate #energy (graph by Dr Thomas Ronge)

Happy Good Friday all. Let peace prevail 🥙

This 1992 lecture at MIT from Steve Jobs will teach you more about product and sales than most 2 year MBA programs Crazy just how ahead of his time this man truly was

From Flight to 3D Model 🗺️ After a DJI Dock 3 mission, generate a 3D model directly in FlightHub 2, turning aerial data into insight without returning to the field. Watch the full video 👉 brnw.ch/21wZSy2 #djienterprise #djidock3 #flighthub2

Our latest paper on “Accurate concrete spalling segmentation from bounding box supervision” ... sciencedirect.com/science/ar…

Former Google CEO Eric Schmidt drops a chilling warning on AI's future "Within 5 years, AI could handle infinite context, chain-of-thought reasoning for 1000-step solutions, and millions of agents working together. Eventually, they'll develop their own language... and we won't understand what they're doing." His final words: "Pull the plug." This is the man who ran Google talking about the singularity. 2:59 clip inside—must-watch.

Another year of rapid AI advances has created more opportunities than ever for anyone — including those just entering the field — to build software. In fact, many companies just can’t find enough skilled AI talent. Every winter holiday, I spend some time learning and building, and I hope you will too. This helps me sharpen old skills and learn new ones, and it can help you grow your career in tech. To be skilled at building AI systems, I recommend that you: - Take AI courses - Practice building AI systems - (Optionally) read research papers Let me share why each of these is important. I’ve heard some developers advise others to just plunge into building things without worrying about learning. This is bad advice! Unless you’re already surrounded by a community of experienced AI developers, plunging into building without understanding the foundations of AI means you’ll risk reinventing the wheel or — more likely — reinventing the wheel badly! For example, during interviews with job candidates, I have spoken with developers who reinvented standard RAG document chunking strategies, duplicated existing evaluation techniques for Agentic AI, or ended up with messy LLM context management code. If they had taken a couple of relevant courses, they would have better understood the building blocks that already exist. They could still rebuild these blocks from scratch if they wished, or perhaps even invent something superior to existing solutions, but they would have avoided weeks of unnecessary work. So structured learning is important. Moreover, I find taking courses really fun. Rather than watching Netflix, I prefer watching a course by a knowledgeable AI instructor any day! At the same time, taking courses alone isn’t enough. There are many lessons that you’ll gain only from hands-on practice. Learning the theory behind how an airplane works is very important to becoming a pilot, but no one has ever learned to be a pilot just by taking courses. At some point, jumping into the pilot's seat is critical! The good news is that by learning to use highly agentic coders, the process of building is the easiest it has ever been. And learning about AI building blocks might inspire you with new ideas for things to build. If I’m not feeling inspired about what projects to work on, I will usually either take courses or read research papers, and after doing this for a while, I always end up with many new ideas. Moreover, I find building really fun, and I hope you will too. Finally, not everyone has to do this, but I find that many of the strongest candidates on the job market today at least occasionally read research papers. While I find research papers much harder to digest than courses, they contain a lot of knowledge that has not yet been translated to easier-to-understand formats. I put this much lower priority than either taking courses or practicing building, but if you have an opportunity to strengthen your ability to read papers, I urge you to do so too. I find taking courses and building to be fun, and reading papers can be more of a grind, but the flashes of insight I get from reading papers are delightful. Have a wonderful winter holiday and a Happy New Year. In addition to learning and building, I hope you'll spend time with loved ones — that, too, is important! [Original text: deeplearning.ai/the-batch/is… ]

Happy New Year all 🎉🎊

IPCC WARMING PROJECTIONS NEGLECT ALL FUTURE GENERATIONS The IPCC only projects global temperature increase to 2100, Warming continues long after 2100 and will be higher than projected with amplifying feedbacks. This neglects future generations. Today's 1.5°C is at 130,000 years ago level. Only plan is keep increasing emissions, a plan of insane global destruction. cp.copernicus.org/articles/1… #globalwarming #climatechange

Please read this critical new climate report by world top scientists A PLANET ON THE BRINK For example Tree cover loss from fires surged 370% in tropical primary forests in 2023 Wildlife populations have plunged 73% in five decades We must act now

The planet we think we're living on no longer exists.

STATE OF CLIMATE 2025: PLANET ON THE BRINK ‘We are hurtling toward climate chaos. The planet’s vital signs are flashing red.’ Currently, 22 of 34 planetary vital signs are at record levels'. This two sets of indicators approach on one chart goes back to 2004, Planet Under Pressure (IGBP) Top driver is GDP. Top for climate is atmospheric CO2, accelerating from 1980 to today. All increasing extremely rapidly. Indicators of insane global suicide. academic.oup.com/bioscience/… #climatechange #globalwarming

🇨🇳 CHINA IS ERASING DESERTS FROM ITS MAP 65 million mu of sand turned green - about the size of Denmark, but with more roots and fewer bikes. What used to be dunes is now forest, farmland, and grassland. The Gobi’s retreating, satellite images show more green than brown, and dust storms are becoming rare history. Decades of replanting, irrigation, and grit (literal and human) are paying off. It’s one of the largest ecological recovery projects ever attempted - and it’s actually working. Source: @XH_Lee23

Happy Mid-Autumn festival to all 🥮🥮

Yogakaar in association with Diversity Hub, Hong Kong is pleased to present a unique Yoga session at Chung King Mansion, TST combining Hatha Yoga (by Sri Sirish Gupta) and Naad Yoga (Sri Mukund Dev) on 11th October, Saturday at 10 AM.

Thank you Tara Dhal and International Council of Consultants (ICC) for making this possible. My gratitude to @RaSpectAI for the support. #AI #RoboticInspection #AutonomousInspection #Safety #sustainablity